Samuel G. Hanson

Samuel G. Hanson is a Marvin Bower Associate Professor in the Finance Unit at Harvard Business School, and a Faculty Research Fellow at the National Bureau of Economic Research. He teaches the Investment Strategies course in the MBA elective curriculum and PhD courses in Corporate Finance and Empirical Methods.

Professor Hanson holds a Ph.D. in Business Economics from Harvard University and a B.A. in Quantitative Economics and Philosophy from Tufts University. Before beginning his doctoral studies, he worked as an investment banking analyst at Lehman Brothers and as an assistant economist at the Federal Reserve Bank of New York. During 2009 Hanson worked at the U.S. Treasury Department where he served as a Special Assistant and Liaison to the White House National Economic Council.

Professor Hanson’s research interests lie in corporate finance, behavioral finance, and asset pricing. His recent research has focused on corporate supply responses to fluctuations in investor demand for different types of securities and on optimal financial regulation. Hanson’s research has appeared in the Quarterly Journal of Economics, the Journal of Finance, the Journal of Financial Economics, the Review of Financial Studies, and the Journal of Economic Perspectives.

Publications

Small business lending by the four largest banks fell sharply relative to others in 2008 and remained depressed through 2014. We explore the dynamic adjustment process following this credit supply shock. In counties where the largest banks had a high market share, the aggregate flow of small business credit fell, interest rates rose, fewer businesses expanded, unemployment rose, and wages fell from 2006 to 2010. While the flow of credit recovered after 2010 as other lenders slowly filled the void, interest rates remain elevated. Although unemployment returns to normal by 2014, the effect on wages persists in these areas.

A large literature argues that long-term interest rates appear to react far more to high-frequency (e.g., daily or monthly) movements in short-term interest rates than predicted by the standard expectations hypothesis. We find that, since 2000, such high-frequency "excess sensitivity" remains evident in U.S. data and has, if anything, grown stronger. By contrast, the positive association between low-frequency changes (e.g., at a 6-month or 12-month horizon) in short- and long-term interest rates, which was quite strong before 2000, has weakened substantially in recent years. As a result, "conundrums"—defined as 6- or 12-month periods in which short rates and long rates move in opposite directions—have become far more common since 2000. We argue that the puzzling combination of high-frequency excess sensitivity and low-frequency decoupling between short- and long-term rates can be understood using a model in which (i) shocks to short-term interest rates lead to a rise in term premia on long-term bonds and (ii) arbitrage capital moves slowly over time. We discuss the implications of our findings for interest rate predictability, the transmission of monetary policy, and the validity of high-frequency event study approaches for assessing the impact of monetary policy.

We take stock of the post-crisis financial regulatory reform agenda. We highlight and summarize areas of clear progress, where post-crisis reforms should either be maintained or built upon. We then identify several areas where the new regulations could be streamlined or rolled back in an effort to reduce the burden on the financial sector, particularly on smaller banks.

We develop a model in which capital moves quickly within an asset class, but slowly between asset classes. While most investors specialize in a single asset class, a handful of generalists can gradually reallocate capital across markets. Upon the arrival of a large supply shock, prices of risk in the directly impacted asset class become disconnected from those in others. Over the long run, capital flows between markets and prices of risk become more closely aligned. While prices in the directly impacted market initially overreact to the supply shock, we show that prices in related asset classes underreact under plausible conditions. We use the model to assess event-study evidence on the impact of recent large-scale asset purchases by central banks.

We present a model of credit market sentiment in which investors form beliefs about future creditworthiness by extrapolating past defaults. Our key contribution is to model the endogenous two-way feedback between credit market sentiment and credit market outcomes. This feedback arises because investors’ beliefs depend on past defaults, but beliefs also drive future defaults through investors’ willingness to refinance debt at low interest rates. Our model is able to capture many documented features of credit booms and busts, including the link between credit growth and future returns and the “calm before the storm” periods in which fundamentals have deteriorated but the credit market has not yet turned.

In this paper, we develop a new model for government cost-benefit analysis in the presence of risk. In our model, a benevolent government chooses the scale of a risky project in the presence of two key frictions. First, there are market failures, which cause the government to perceive project payoffs differently than private households do. This gives the government a "social risk management" motive: projects that ameliorate market failures when household marginal utility is high are appealing. The second friction is that government financing is costly because of tax distortions. This creates a "fiscal risk management" motive: incremental spending that occurs when total government spending is already high is particularly unattractive. A first key insight is that the government's need to manage fiscal risk frequently limits its capacity for managing social risk. A second key insight is that fiscal risk and social risk interact in complex ways. When considering many potential projects, government cost-benefit analysis thus acquires the flavor of a portfolio choice problem. We use the model to explore how the relative attractiveness of two technologies for promoting financial stability—bailouts and regulation—varies with the government's fiscal burden and characteristics of the economy.

Collateralized debt obligations (CDOs) and private-label mortgage-backed securities (MBS) backed by nonprime loans played a central role in the recent financial crisis. Little is known, however, about the underlying forces that drove investor demand for these securitizations. Using micro-data on insurers' and mutual funds' bond holdings, we find considerable heterogeneity in investor demand for securitizations in the pre-crisis period. We argue that both investor beliefs and incentives help to explain this variation in demand. By contrast, our data paints a more uniform picture of investor behavior in the crisis. Consistent with theories of optimal liquidation, investors largely traded in more liquid securities, such as government-guaranteed MBS, to meet their liquidity needs during the crisis.

We propose three core principles that should inform the design of bank capital regulation. First, wherever possible, multiple constraints on the minimum level of equity capital should be consolidated into a single constraint. This helps to avoid a distortionary situation where different constraints bind for different banks performing the same activity. Second, while a regulatory framework that relies primarily on minimum capital ratios is appropriate for normal times, such a framework is inadequate in the wake of a large negative shock to the system. Following an adverse shock, it becomes critical to emphasize dynamic resilience, which involves forcing banks to actively recapitalize—i.e., regulation needs to focus on getting banks to raise new dollars of equity capital, rather than just maintaining their capital ratios. Third, the best way to deal with the inevitable gaming of any set of ex ante capital rules is not to propose further rules, but rather to allow the regulator sufficient flexibility to address unforeseen contingencies ex post. We use these principles to suggest a number of modifications to the current set of risk-based capital requirements, to the leverage ratio, and to the Federal Reserve’s stress-testing framework.

Many have argued that overoptimistic thinking on the part of lenders helps fuel credit booms. We use new microdata on mutual funds' holdings of securitizations to examine which investors are susceptible to such boom-time thinking. We show that firsthand experience plays a key role in shaping investors' beliefs. During the 2003–2007 mortgage boom, inexperienced fund managers loaded up on securitizations linked to nonprime mortgages, accumulating twice the holdings of more seasoned managers. Moreover, inexperienced managers who personally experienced severe or recent adverse investment outcomes behaved more like seasoned managers. Training and institutional memory can serve as partial substitutes for personal experience.

U.S. money market mutual funds (MMFs) are an important source of dollar funding for global financial institutions, particularly those headquartered outside the U.S. MMFs proved to be a source of considerable instability during the financial crisis of 2007–2009, resulting in extraordinary government support to help stabilize the funding of global financial institutions. In light of the problems that emerged during the crisis, a number of MMF reforms have been proposed, which we analyze in this paper. We assume that the main goal of MMF reform is safeguarding global financial stability. In light of this goal, reforms should reduce the ex ante incentives for MMFs to take excessive risk and increase the ex post resilience of MMFs to system-wide runs. Our analysis suggests that requiring MMFs to have subordinated capital buffers could generate significant financial stability benefits. Subordinated capital provides MMFs with loss absorption capacity, lowering the probability that an MMF suffers losses large enough to trigger a run, and reduces incentives to take excessive risks. Other reform alternatives based on market forces, such as converting MMFs to a floating NAV, may be less effective in protecting financial stability. Our analysis sheds light on the fundamental tensions inherent in regulating the shadow banking system. U.S. money market mutual funds (MMFs) are an important source of dollar funding for global financial institutions, particularly those headquartered outside the United States. MMFs proved to be a source of considerable instability during the financial crisis of 2007–2009, resulting in extraordinary government support to help stabilize the funding of global financial institutions. In light of the problems that emerged during the crisis, a number of MMF reforms have been proposed, which we analyze in this paper. We assume that the main goal of MMF reform is safeguarding global financial stability. In light of this goal, reforms should reduce the ex-ante incentives for MMFs to take excessive risk and increase the ex post resilience of MMFs to system-wide runs. Our analysis suggests that requiring MMFs to have subordinated capital buffers could generate significant financial stability benefits. Subordinated capital provides MMFs with loss absorption capacity, lowering the probability that an MMF suffers losses large enough to trigger a run and reduces incentives to take excessive risks. Other reform alternatives based on market forces, such as converting MMFs to a floating NAV, may be less effective in protecting financial stability. Our analysis sheds light on the fundamental tensions inherent in regulating the shadow banking system.

We examine the business model of traditional commercial banks when they compete with shadow banks. While both types of intermediaries create safe "money-like" claims, they go about this in different ways. Traditional banks create money-like claims by holding illiquid fixed-income assets to maturity, and they rely on deposit insurance and costly equity capital to support this strategy. This strategy allows bank depositors to remain "sleepy": they do not have to pay attention to transient fluctuations in the market value of bank assets. In contrast, shadow banks create money-like claims by giving their investors an early exit option requiring the rapid liquidation of assets. Thus, traditional banks have a stable source of funding, while shadow banks are subject to runs and fire-sale losses. In equilibrium, traditional banks have a comparative advantage at holding fixed-income assets that have only modest fundamental risk but are illiquid and have substantial transitory price volatility, whereas shadow banks tend to hold relatively liquid assets.

We study the link between investment boom and bust cycles and returns on capital in the dry bulk shipping industry. We show that high current ship earnings are associated with high used ship prices and heightened industry investment in new ships, but forecast low future returns. We propose and estimate a behavioral model of industry cycles that can account for the evidence. In our model, firms over-extrapolate exogenous demand shocks and partially neglect the endogenous investment response of their competitors. As a result, firms overpay for ships and overinvest in booms and are disappointed by the subsequent low returns. Formal estimation of the model suggests that modest expectational errors can result in dramatic excess volatility in prices and investment.

Changes in monetary policy have surprisingly strong effects on forward real rates in the distant future. A 100 basis point increase in the two-year nominal yield on a Federal Open Markets Committee announcement day is associated with a 42 basis point increase in the ten-year forward real rate. This finding is at odds with standard macro models based on sticky nominal prices, which imply that monetary policy cannot move real rates over a horizon longer than that over which all prices in the economy can readjust. Instead, the responsiveness of long-term real rates to monetary shocks appears to reflect changes in term premia. One mechanism that could generate such variation in term premia is based on demand effects due to the existence of what we call yield-oriented investors. We find some evidence supportive of this channel.

We study optimal government debt maturity in a model where investors derive monetary services from holding riskless short-term securities. In a setting where the government is the only issuer of such riskless paper, it trades off the monetary premium associated with short-term debt against the refinancing risk implied by the need to roll over its debt more often. We then extend the model to allow private financial intermediaries to compete with the government in the provision of short-term, money-like claims. We argue that if there are negative externalities associated with private money creation, the government should tilt its issuance more towards short maturities. The idea is that the government may have a comparative advantage relative to the private sector in bearing refinancing risk and, hence, should aim to partially crowd out the private sector's use of short-term debt.

Most home mortgages in the United States are fixed-rate loans with an embedded prepayment option. When long-term rates decline, the effective duration of mortgage-backed securities (MBS) falls due to heightened refinancing expectations. I show that these changes in MBS duration function as large-scale shocks to the quantity of interest rate risk that must be borne by professional bond investors. I develop a simple model in which the risk tolerance of bond investors is limited in the short run, so these fluctuations in MBS duration generate significant variation in bond risk premia. Specifically, bond risk premia are high when aggregate MBS duration is high. The model offers an explanation for why long-term rates could appear to be excessively sensitive to movements in short rates and explains how changes in MBS duration act as a positive-feedback mechanism that amplifies interest rate volatility. I find strong support for these predictions in the time series of US government bond returns.

We develop a novel methodology to infer the amount of capital allocated to quantitative equity arbitrage strategies. Using this methodology, which exploits time-variation in the cross section of short interest, we document that the amount of capital devoted to value and momentum strategies has grown significantly since the late 1980s. We provide evidence that this increase in capital has resulted in lower strategy returns. However, consistent with theories of limited arbitrage, we show that strategy-level capital flows are influenced by past strategy returns as well as strategy return volatility, and that arbitrage capital is most limited during times when strategies perform best. This suggests that the growth of arbitrage capital may not completely eliminate returns to these strategies.

We show that the credit quality of corporate debt issuers deteriorates during credit booms, and that this deterioration forecasts low excess returns to corporate bondholders. The key insight is that changes in the pricing of credit risk disproportionately affect the financing costs faced by low quality firms, so the debt issuance of low quality firms is particularly useful for forecasting bond returns. We show that a significant decline in issuer quality is a more reliable signal of credit market overheating than rapid aggregate credit growth. We use these findings to investigate the forces driving time-variation in expected corporate bond returns.

We present a model that helps explain several past collapses of securitization markets. Originators issue too many informationally insensitive securities in good times, blunting investor incentives to become informed. The resulting endogenous scarcity of informed investors exacerbates primary market collapses in bad times. Inefficiency arises because informed investors are a public good from the perspective of originators. All originators benefit from the presence of additional informed investors in bad times, but each originator minimizes his reliance on costly informed capital in good times by issuing safe securities. Our model suggests regulations that limit the issuance of safe securities in good times.

Non-parametric estimators of treatment effects are often applied in settings where clustering may be important. We provide a general methodology for consistently estimating the variance of a large class of non-parametric estimators, including the simple matching estimator, in the presence of clustering. Software for implementing our variance estimator is available in Stata.

We show that characteristics of stock issuers can be used to forecast important common factors in stocks' returns such as those associated with book-to-market, size, and industry. Specifically, we use differences between the attributes of stock issuers and repurchasers to forecast characteristic-related factor returns. For example, we show that large firms underperform following years when issuing firms are large relative to repurchasing firms. While our strongest results are for portfolios based on book-to-market, size (i.e., we forecast the HML and SMB factors), and industry, our approach is also useful for forecasting factor returns associated with distress, payout policy, and profitability.

We argue that time-series variation in the maturity of aggregate corporate debt issues arises because firms behave as macro liquidity providers, absorbing the large supply shocks associated with changes in the maturity structure of government debt. We document that when the government funds itself with relatively more short-term debt, firms fill the resulting gap by issuing more long-term debt, and vice-versa. This type of liquidity provision is undertaken more aggressively: i) in periods when the ratio of government debt to total debt is higher; and ii) by firms with stronger balance sheets. Our theory provides a new perspective on the apparent ability of firms to exploit bond-market return predictability with their financing choices.

This paper examines the impact of neglected heterogeneity on credit risk. We show that neglecting heterogeneity in firm returns and/or default thresholds leads to under estimation of expected losses (EL), and its effect on portfolio risk is ambiguous. Once EL is controlled for, the impact of neglecting parameter heterogeneity is complex and depends on the source and degree of heterogeneity. We show that ignoring differences in default thresholds results in overestimation of risk, while ignoring differences in return correlations yields ambiguous results. Our empirical application, designed to be typical and representative, combines both and shows that neglected heterogeneity results in overestimation of risk. Using a portfolio of U.S. firms we illustrate that heterogeneity in the default threshold or probability of default, measured for instance by a credit rating, is of first order importance in affecting the shape of the loss distribution: including ratings heterogeneity alone results in a 20% drop in loss volatility and a 40% drop in 99.9% VaR, the level to which the risk weights of the New Basel Accord are calibrated.

In this paper we conduct a systematic comparison of confidence intervals around estimated probabilities of default (PD) using several analytical approaches as well as parametric and nonparametric bootstrap methods. We do so for two different PD estimation methods, cohort and duration (intensity), with 22 years of credit ratings data. We find that the bootstrapped intervals for the duration based estimates are relatively tight when compared to either analytic or bootstrapped intervals around the less efficient cohort estimator. We show how the large differences between the point estimates and confidence intervals of these two estimators are consistent with non-Markovian migration behavior. Surprisingly, even with these relatively tight confidence intervals, it is impossible to distinguish notch-level PDs for investment grade ratings, e.g. a PDAA- from a PDA+. However, once the speculative grade barrier is crossed, we are able to distinguish quite cleanly notch-level estimated PDs. Conditioning on the state of the business cycle helps: it is easier to distinguish adjacent PDs in recessions than in expansions.

We present a model of the yield curve in which the central bank can provide market participants with forward guidance on both future short rates and on future Quantitative Easing (QE) operations, which affect bond supply. Forward guidance on short rates works through the expectations hypothesis, while forward guidance on QE works through expected future bond risk premia. If a QE operation is expected to be undone in the near term, then its announcement will have a hump-shaped effect on the yield and forward-rate curves; otherwise, the effect may be increasing with maturity. Humps associated to QE announcements typically occur at maturities longer than those associated to short-rate announcements, even when the effects of the former are expected to last over a shorter horizon. We use our model to re-examine the empirical evidence on QE announcements in the United States.

We argue that the Federal Reserve should use its balance sheet to help reduce a key threat to financial stability: the tendency for private-sector financial intermediaries to engage in excessive amounts of maturity transformation—i.e., to finance risky assets using dangerously large volumes of runnable short-term liabilities. Specifically, we make the case that the Fed can complement its regulatory efforts on the financial-stability front by maintaining a relatively large balance sheet, even when policy rates have moved well away from the zero lower bound (ZLB). In so doing, it can help ensure that there is an ample supply of government-provided safe short-term claims—e.g., interest-bearing reserves and reverse repurchase agreements (RRP). By expanding the overall supply of safe short-term claims, the Fed can weaken the market-based incentives for private sector intermediaries to issue too many of their own short-term liabilities. And crucially, we argue that the Fed can crowd out private-sector maturity transformation in this way without compromising the ability of conventional monetary policy to focus on its traditional dual mandate of promoting maximum employment and stable prices.

We examine the impact of "substantially heightened" capital requirements on large financial institutions, and on their customers. Our analysis yields three main conclusions. First, the frictions associated with raising new external equity finance are likely to be greater than the ongoing costs of holding equity on the balance sheet, implying that the new requirements should be phased in gradually. Second, the long-run steady-state impact on loan rates is likely to be modest, in the range of 25 to 45 basis points for a ten percentage-point increase in the capital requirement. Third, due to the unique nature of competition in financial services, even these modest effects raise significant concerns about migration of credit-creation activity to the shadow-banking sector, and the potential for increased fragility of the overall financial system that this might bring. Thus to avoid tilting the playing field in such a way as to generate a variety of damaging unintended consequences, increased regulation of the shadowbanking sector should be seen as an important complement to the reforms that are contemplated for banks and other large financial institutions.

This paper explores the question of whether hedge funds engage in frontrunning strategies that exploit the predictable trades of others. One potential opportunity for front-running arises when distressed mutual funds—those suffering large outflows of assets under management—are forced to sell stocks they own. We document two pieces of evidence that are consistent with hedge funds taking advantage of this opportunity. First, in the time series, the average returns of long/short equity hedge funds are significantly higher in those months when a larger fraction of the mutual-fund sector is in distress. Second, at the individualstock level, short interest rises in advance of sales by distressed mutual funds.

Investment manager Eliza Baena confronts an apparent convertible bond arbitrage opportunity when she notices a narrowing spread between two Boston Properties (BXP) bonds, one a convertible bond and the other a straight bond, in the wake of the 2008 Lehman bankruptcy. Baena must decide if there is an opportunity, how to structure a trade to exploit it, and how much of her fund's capital to allocate. Case exposition includes descriptions of basic financing arrangements that support arbitrage strategies, such as rehypothecation and margin lending.

In June 2015 William A. Ackman, the CEO and founder of New York hedge fund Pershing Square Capital, reflects on the success of the fund he has spent over a decade building. Since its inception in 2004, Pershing Square's assets under management had grown from $500 million to well over $18 billion. Ackman is now considering a sizable new portfolio position and must decide how he should raise capital to undertake this new investment. This choice is affected by the recent launch of his new, $6 billion closed-end vehicle, Pershing Square Holdings, as well as the firm's lengthening investment horizon. Although always activist in nature, Ackman and his fund had in recent years become substantively involved in the management of portfolio companies, often working to drive shareholder value by improving operating performance.

Longbow Capital Partners is a value-oriented long/short hedge fund focused on stocks in the energy sector. In January 2011, Longbow had invested in NiSource, a Fortune 500 company that owns a diverse portfolio of regulated energy businesses. In late 2014, Longbow was deciding whether or not to maintain its position in NiSource. To make this decision, students must perform a discounted dividend analysis to determine the fundamental value of NiSource's stock. Students are also asked to perform a sum-of-the-parts analysis to assess the implications of NiSource's recent proposal to pursue a tax-advantaged spin-off of its pipeline business.

This case describes the Dogs of the Dow investment strategy, value investing, and using dividend yields as a means to determine intrinsic value. It also describes exchange traded notes and a particular exchange traded note, known as the Dogs of the Dow, which tracks the performance of the 10 highest yielding stocks of the 30 stocks that make up the Dow Jones Industrial Average (DJIA). The case provides share price data, dividend data, and financial statement data on the 30 DJIA companies to enable students to perform their own calculations.